## 0. IMPORT LIBRARIES

Ignore warnings

## 1. READ DATA
## 2. EDA - Exploratory Data Analysis

Data Visulization

Coherence Checking

Remove observations out of the rules

Correlations

## 3. PREPROCESSING DATA

Missing Values

Manualy verify Outliers

CustMonVal

MonthSal

ClaimsRate

PremMotor

PremHousehold

PremHealth

PremLife

PremWork

Outliers

Isolation Forest

Minimum Covariance Determinant

PCA visualization of Outliers

## Transforming variables

New variables Outliers

New variables correlations

## Feature Selection

Standardaization

Select the best features

## Modelling

We implemented the following clustering algorithms:

K-means


Self-Organizing Maps(SOM) + K-means


Self-Organizing Maps (SOM) + HC


MiniBatchKMeans


GMM


BIRCH


HC


DBSCAN


Calculating R-squared metrics


Multiple Correspondence Analysis (MCA)